(238e) A Semi-Physical Valve Stiction Model and Its Application for Stiction Quantification

A
semi-physical valve stiction model and its application for stiction quantification

Q. Peter He¹ and Jin Wang²

¹Department of Chemical
Engineering, Tuskegee University, Tuskegee, AL 36088, USA

²Department of Chemical
Engineering, Auburn University, Auburn, AL 36849, USA

Valve
stiction is one of the most common equipment problems that can cause poor
performance in control loops. Consequently, there is a strong need in the
process industry for non-invasive methods that can not only detect but also quantify
stiction [1].

To
simulate valve stiction, both detailed physical models and empirical models
have been developed. Physical models [2] describe the stiction phenomenon using
force balances based on Newton's second law of motion. The main disadvantage of
these models is that they require knowledge of several parameters such as the
mass of the moving parts and different type of friction forces which cannot be
easily measured and depend on the type of fluid and valve wear. On the other
hand, empirical or data-driven models [3-5] use simple empirical relationships
between valve input and output to describe valve stiction, with just a few
parameters that can be determined from operating data. Due to their simplicity
and easy implementation, data-driven models have gained tremendous research
interest in recent years.

In
this work, a semi-physical valve stiction model is derived based on the analysis
of the dynamic response of a physical model of a pneumatic valve, which is
derived based on the Newton's second law of motion [6]. Comparison of the
semi-physical model with the three existing data-driven models [3-5] to the
physical model [2] shows that only the semi-physical model can reproduce the
same valve behavior described by the physical model. One advantage of the
semi-physical model is that it contains only two parameters compared to eight
parameters of the physical model. Another advantage of the semi-physical model
is that its implementation is straightforward without the involvement of cumbersome
numerical integration as in the physical model.

In
addition, we propose a noninvasive valve stiction quantification method based
on the semi-physical model using the routine operating data obtained from the
process, i.e., process variable (PV) and controller output (OP). The algorithm
is proposed to estimate the stiction parameters, namely static friction f_S
and dynamic or kinetic friction f_D, without requiring the valve
position (VP) signal. Identification is accomplished by using linear and
nonlinear least-squares methods which are robust and easy to implement. Several
simulation and industrial examples, including both self-regulating and
integrating processes with different degrees of stiction, are used to
demonstrate the effectiveness of the method.

Key
words: valve modeling, stiction quantification; control valve; identification
and estimation; fault diagnosis

1. Choudhury, M. S.; Shah, S.; Thornhill, N.; Shook, D. Automatic detection and quantification of stiction in control valves. Control Engineering Practice 2006, 14, 1395-1412.
2. Kayihan A, Doyle III FJ (2000) Friction compensation for a process control valve. Control Engineering Practice 8:799?812.
3. He QP,Wang J, PottmannM, Qin SJ (2007) A curve fitting method for detecting valve stiction in oscillating control loops. Industrial and Engineering Chemistry Research 46:4549?4560.
4. Choudhury MAAS, Thornhill NF, Shah SL (2005) Modeling valve stiction. Control Engineering Practice 13:641?658.
5. Kano, M., Maruta, H., Kugemoto, H., Shimizu, K. (2004). Practical model and detection algorithm for valve stiction. Proc IFAC DYCOPS, Cambridge, USA.
6. He, Q.P., Wang, J. & Qin, S.J. (2010), An alternative stiction modeling approach and comparison of different stiction models, in Detection and Diagnosis of Stiction in Control Loops ? State of the Art and Advanced Methods, Jelali, M. and Huang, B. (Eds.), Springer, pp37-60